Data Analysis Training, Uyo, Akwa Ibom State.

Data Analysis and Visualization Training, Uyo, Akwa Ibom State and Port Harcourt, Rivers State.

Data Analysis and Visualization Training and Certification

Course Objectives:

• Develop proficiency in data visualization tools (Power BI, Tableau)
• Master data analysis tools (SPSS, Excel, EViews, MiniTab)
• Learn Python programming and its libraries (NumPy, Pandas, SciPy)
• Gain expertise in data management tools (SQL, MongoDB, Cassandra)
• Equip yourself for data jobs like collection, cleaning, analysis, BI, and ML
• Understand predictive modeling and machine learning algorithms
• Explore deep learning techniques for unstructured data

Course Outline:

Module 1: Introduction to Data Analytics 

• What is data analytics?
• The importance of data analytics in today’s world
• The different types of data analytics
• The data analytics lifecycle
• Applications of data analytics across various industries

Module 2: Data Visualization Essentials 

• The power of data visualization
• Choosing the right chart for your data
• Creating effective data visualizations with Power BI
• Mastering data visualization techniques in Tableau

Module 3: Data Analysis Fundamentals 

• Understanding data types and distributions
• Descriptive statistics and data cleaning
• Introduction to hypothesis testing and correlation analysis
• Regression analysis and forecasting techniques

Module 4: Introduction to Python Programming 

• Python basics: variables, data types, operators, and control flow
• Functions and modules in Python
• Object-oriented programming in Python
• Working with files and databases in Python

Module 5: Python Libraries for Data Analysis 

• NumPy: efficient numerical computing
• Pandas: data structures and analysis
• SciPy: scientific computing and advanced algorithms
• Matplotlib and Seaborn: data visualization with Python

Module 6: Advanced Data Analysis Techniques 

• Time series analysis and forecasting
• Dimensionality reduction and feature engineering
• Clustering and classification algorithms
• Machine learning for predictive modeling

Module 7: Introduction to Deep Learning

• Artificial neural networks and deep learning fundamentals
• Convolutional neural networks (CNNs) for image recognition
• Recurrent neural networks (RNNs) for natural language processing
• Deep learning applications in various fields

Module 8: Data Management and Storage 

• SQL: querying and manipulating databases
• MongoDB: NoSQL databases for unstructured data
• Apache Cassandra: distributed database for high availability

Module 9: Data Collection and Cleaning

• Techniques for data collection from various sources
• Data cleaning and preprocessing techniques
• Data quality management and best practices

Module 10: Business Intelligence and Reporting 

• Building dashboards and reports with Power BI
• Data storytelling and communication
• Business intelligence applications for decision making

Module 11: Career Opportunities in Data Analytics 

• Identifying potential data analytics jobs
• Building a strong resume and portfolio
• Interview preparation and career development tips

Module 12: Hands-on Projects and Case Studies 

• Real-world data projects using various tools and techniques
• Applying data analytics to solve business problems
• Case studies of successful data analytics implementations

Assessment:

• Daily Class Tasks
• Weekly Project Presentations
• Continuous assessment through quizzes and assignments on over 73 Case-Studies
• Mid-term and final examinations
• Final Project presentations and portfolio development

Certification:

Upon successful completion of the course, participants will receive a certificate of completion

We also assist you with career guidance and job placement assistance.

Wedigraf Tech Hub

69, Abak Road, by Udo Abasi Street, Uyo, Akwa Ibom State.

(First Floor, LG Building, beside Pepperoni)